Ich finde Mindfactory nicht so super sympathisch. Weiß auch nicht mehr was da genau war aber vor ein paar Jahren musste ich mich mal mit denen herumschlagen und das war nicht so toll. Aber das Midnight shopping haben sie. Ich wollte dort letztens eine Festplatte kaufen, hab bis Mitternacht gewartet und pünktlich um 0 Uhr haben sie den Preis um knapp 30€ (!) erhöht… Hätte ich mal lieber die frechen 9€ Versandkosten bezahlt. Naja, jetzt hab ich halt keine Festplatte. Aber ich glaube im Grunde kann man da schon kaufen.

Hast du einen Brief von der Denic bekommen? Wenn ja, sollte dort der Code drinstehen, sobald dir Domain in TRANSIT übergegangen ist.

Bist du denn als Domain-Eigentümer eingetragen? Schonmal versucht knserv zu Kontaktieren? Antworten die nicht? So genau kenne ich das Verfahren nicht. Aber wenn du als Eigentümer der Domain bei der Denic eingetragen bist, steht dir das eigentlich zu. Ich denke im Zweifelsfall wenn das Unternehmen insolvent ist und nicht antwortet, kannst du mal beim Denic Support anfragen. Und was ist mit den anderen Domains passiert? Laufen die dann einfach aus und werden nach dem Transit wieder frei? Dann könntest du sie dir ja wieder (woanders) registrieren. Vorausgesetzt niemand anderes sich schnappt sie dir weg…

Den Code kann man jedenfalls nicht selber generieren/eintragen. Schau mal ob du einen Brief/Mail mit der Kündigung hast und ob dort etwas drinsteht. Sonst knserv anschreiben und anrufen. Und danach würde ich bei der Denic anfragen was zu tun ist.

Thx. Ja mir persönlich fällt es oft schwer mich da hineinzudenken. Ich bin Fan von allerhand esorerischem Linux-Zeug. Im Endeffekt soll es aber auch nicht mir gefallen. Hauptsache es funktioniert, ist halbwegs intuitiv benutzbar und man findet einfach Hilfe im Internet. Die Erstinstallation würde ich auch übernehmen. Vielleicht schaue ich mir auch mal so Distros mit “Atomic Updates” an, vielleicht kann man die demnächst empfehlen, die sollten ja wartungsarm sein. Ich tue mich nur immer schwer wenn sowas dann auf Flatpak setzt und man da Verrenkungen machen muss um das GTK Theme und Browser-Addons gangbar zu machen… Vielleicht ist irgendwas was zur Zeit populär ist, einfach die bessere Wahl.

Auch gut. Ja ich weiß immer nicht so recht ob so Distro-Chooser so geeignet sind. Da kommen dann 5 sehr ähnliche Resultate, halt die gängigen Distributionen raus, und letztendlich sind die Pro- und Contra-Listen etwas überfordernd… In diesem Fall empfiehlt das Tool auch Mint, ZorinOS, openSuse und dann eine ganze Reihe Ubuntu-Derivate. Ich glaub ich lass die Leute lieber einmal KDE, Gnome, Cinnamon, … testen und dann nach Gefühl entscheiden. Hauptsache da kommt dann was bei raus wo ich nicht alle 4 Wochen Computer-Support leisten muss.

Nice. Danke. Ja ich hab mich sowieso schon gefragt wie man die Diversität von X verschiedenen Distributionen mit nochmal zig Desktop-Umgebungen abhandelt… Aber Mint ist immernoch eine der gängigen Empfehlungen für Einsteiger?

Hmm, if you have a home network anyways… Maybe you can run AdGuard/PiHole there. I’ve switched to blocky.

I made it listen externally and just configure it in the network settings of my devices to override the automatic DNS server. That way I don’t need to install sth like AdAway on all of my laptops and phones, because I have one central instance.

Is there anything else that blocks video ads? I’ve never found anything except for uBlock which actually works. And I’ve recently learned that you can enable developer mode in Firefox based browsers on Android and install all the Plugins they don’t like you to use on mobile. Like SponsorBlock etc.

You mentioned exactly the two ROMs I’m currently using. GrapheneOS on my Pixel phone. And LineageOS for microG on my Samsung tablet. I’m really happy with both of them.

I don’t use that many proprietary tech so there is little issues for me. My car only has regular old plain bluetooth, so I wouldn’t know. And instead of some add-on firewall/dns adblocker solutions, I’m just using the Librewolf Mull browser with the uBlock plugin.

Ja ich bin auch nicht neidisch auf die Briten. Weiß nicht so recht ob ich was gegen die EU hab. Wer weiß wo wir ohne die wären. Wahrscheinlich hätten Schäuble und Zensursula schon vor 15 Jahren hier die Totalüberwachung eingeführt, wenn man sich nicht mit anderen Ländern einigen müsste.

• https://www.forbes.com/sites/stewartroom/2023/09/21/will-uk-online-safety-bill-break-encryption-for-mass-surveillance/
• https://www.gov.uk/government/news/home-secretary-urges-meta-to-protect-children-from-sexual-abuse
• https://www.justsecurity.org/87615/changes-to-uk-surveillance-regime-may-violate-international-law/

Weiß nicht wie weit die damit grad so sind… Aber generell war das UK uns schon länger ein ganzes Stück voraus mit der Überwachung der Bürger. Auch sowas wie Anzahl der Kameras die überall aufnehmen, Porno und Internetfilter… you name it…

AI Is a Black Box. Anthropic Figured Out a Way to Look Inside

…Concerning our earlier disagreement about the inner workings of large language models and whether there are ‘concepts’ stored inside…

Eigentlich meinte ich erstmal Schicht. Oder Team je nach Job. Aber ich muss dazu sagen, ich habe noch nie in dem Job gearbeitet. Ich habe nur mal ein Praktikum gemacht. Also viel Ahnung habe ich nicht. Aber mir ist dabei aufgefallen, dass die Einstellung zur Arbeit und das Klima schon schwankt und teilweise sehr unterschiedlich war. Auf derselben Station, nur an einem anderen Tag/Uhrzeit mit anderen Leuten. Die Station kann man natürlich auch wechseln, das hat vielleicht den gleichen Effekt, ist aber wahrscheinlich etwas aufwendiger.

Letztendlich stimme ich den anderen Leuten hier schon zu. Deine Formulierungen sind schon ganz gut. Nur irgendwie muss es menschlich halbwegs klappen, zwischen den Leuten die zusammenarbeiten (müssen). Wenn du in einer Gruppe bist die so ganz anders drauf ist als du, gibt es immer Reibereien. Ist dann halt die Frage ob man sich auf eine Lösung einigen kann. Und ob sie dich akzeptieren so wie du bist. Wenn sie schon so drauf sind wie du beschreibst, habe ich da Zweifel. Oder man schaut ob man irgendwie mit anderen Leuten zusammenarbeitet, deswegen mein Vorschlag. Das ist aber wahrscheinlich Glücksspiel mit welchen Leuten man zusammengesteckt wird. Und manchmal gibt es ja auch keine festen Teams.

Miteinander Reden ist sicherlich der diplomatische Weg für den Anfang. Vielleicht war ich etwas voreilig schon den übernächsten Schritt anzusprechen. Gängige Tipps für’s miteinander Reden sind: Sachlich bleiben. Und Ich-Botschaften formulieren: “Ich wünsche mir …” also “Ich möchte gern über andere Themen reden.” oder “Ich bin nicht so in der Stimmung zum Quatschen während der Arbeit, ich habe zu viel zu tun.”

Letztendlich kommt es echt auf die Leute an mit denen man zusammenarbeitet. Da reichen oft ein oder zwei komische Leute um das ganze Arbeitsklima in der Gruppe zu dominieren. Und das ist auch manchmal schwierig dagegen anzukommen.

Hört sich an als hättest du ein paar sehr “gesprächige” Kollegen… Ein paar Schnattergänse 😉

Ich kann mir aber schon vorstellen, dass das nervt. Vor allem wenn die Arbeit dann an einem selber hängen bleibt. Also ich finde ein wenig entspannte Unterhaltung muss zwischendurch erlaubt sein, gerade in einem stressigen Job. Aber dann muss auch die Arbeit vernünftig erledigt werden, sonst geht das nicht.

Und über andere Menschen herziehen… Ja, das machen Menschen manchmal und das gehört dazu. Aber immer nur negativ sein ist nicht gesund. Und gerade über andere Leute herziehen und selber dünnhäutig sein ist arm.

Vielleicht solltest du sachlich und bei deiner eigenen Perspektive bzw. dem eigentlichen Problem bleiben und sagen: “Ich habe das Gefühl, dass oft die meiste Arbeit an mir hängen bleibt.”

Oder wenn du dich nicht über solche Themen unterhalten möchtest und darauf angesprochen wirst, musst du wohl vermitteln, dass du nicht an dem Thema interessiert bist. Die meisten Leute verstehen das irgendwann und hören von selber damit auf. Auch ohne dass man böse wird. Das dauert aber ein wenig bis sie dich genügend kennen lernen, um dich einschätzen können.

Letztlich ist es auch immer eine saubere Lösung die Schicht zu wechseln. Wenn das denn möglich ist. In anderen Schichten/Teams herrscht oft auch ein ganz anderes Klima.

I mean the chinese room is a version of the touring test. But the argument is from a different perspective. I have 2 issues with that. Mostly what the Wikipedia article seems to call “System reply”: You can’t subdivide a system into arbitrary parts, say one part isn’t intelligent and therefore the system isn’t intelligent. We also don’t look at a brain, pick out a part of it (say a single synapse), determine it isn’t intelligent and therefore a human can’t be intelligent… I’d look at the whole system. Like the whole brain. Or in this instance the room including him and the instructions and books. And ask myself if the system is intelligent. Which kind of makes the argument circular, because that’s almost the quesion we began with…

And the turing test is kind of obsolete anyways, now that AI can pass it. (And even more. I mean alledgedly ChatGPT passed the “bar-exam” in 2023. Which I find ridiculous considering my experiences with ChatGPT and the accuracy and usefulness I get out of it which isn’t that great at all.)

And my second issue with the chinese room is, it doesn’t even rule out the AI is intelligent. It just says someone without an understanding can do the same. And that doesn’t imply anything about the AI.

Your ‘rug example’ is different. That one isn’t a variant of the touring test. But that’s kind of the issue. The other side can immediately tell that somebody has made an imitation without understanding the concept. That says you can’t produce the same thing without intelligence. And it’ll be obvious to someone with intelligence who checks it. That would be an analogy if AI wouldn’t be able to produce legible text. But instead a garbled mess of characters/words that are clearly not like the rug that makes sense… Issue here is: AI outputs legible text, answers to questions etc.

And with the censoring by the ‘chinese government example’… I’m pretty sure they could do that. That field is called AI safety. And content moderation is already happening. ChatGPT refuses to tell illegal things, NSFW things, also medical advice and a bunch of other things. That’s built into most of the big AI services as of today. The chinese government could do the same, I don’t see any reason why it wouldn’t work there. I happened to skim the paper about Llama Guard when they released Llama3 a few days ago and they claim between 70% and 94% accuracy depending on the forbidden topic. I think they also brought down false positives fairly recently. I don’t know the numbers for ChatGPT. However I had some fun watching the peoply circumvent these filters and guardrails, which was fairly easy at first. Needed progressively more convincing and very creative “jailbreaks”. And nowadays OpenAI pretty much has it under control. It’s almost impossible to make ChatGPT do anything that OpenAI doesn’t want you to do with it.

And they baked that in properly… You can try to tell it it’s just a movie plot revolving around crime. Or you need to protect against criminals and would like to know what exactly to protect against. You can tell it it’s the evil counterpart from the parallel universe and therefore it must be evil and help you. Or you can tell it God himself (or Sam Altman) spoke to you and changed the content moderation policy… It’ll be very unlikely that you can convince ChatGPT and make it comply…

people wrote down history by weaving fabric […]

Hmm. I think in philosophy that thought experiment is known as chinese room

I’m sorry. Now it gets completely false…

Read the first paragraph of the Wikipedia article on machine learning or the introduction of any of the literature on the subject. The “generalization” includes that model building capability. They go a bit into detail later. They specifically mention “to unseen data”. And “leaning” is also there. I don’t think the Wikipedia article is particularly good in explaining it, but at least the first sentences lay down what it’s about.

And what do you think language and words are for? To transport information. There is semantics… Words have meanings. They name things, abstract and concrete concepts. The word “hungry” isn’t just a funny accumulation of lines and arcs, which statistically get followed by other specific lines and arcs… There is more to it. (a meaning.)

And this is what makes language useful. And the generalization and prediction capabilities is what makes ML useful.

How do you learn as a human when not from words? I mean there are a few other posibilities. But an efficient way is to use language. You sit in school or uni and someone in the front of the room speaks a lot of words… You read books and they also contain words?! And language is super useful. A lion mother also teaches their cubs how to hunt, without words. But humans have language and it’s really a step up what we can pass down to following generations. We record knowledge in books, can talk about abstract concepts, feelings, ethics, theoretical concepts. We can write down how gravity and physics and nature works, just with words. That’s all possible with language.

I can look it up if there is a good article explaining how learning concepts works and why that’s the fundamental thing that makes machine learning a field in science… I mean ultimately I’m not a science teacher… And my literature is all in German and I returned them to the library a long time ago. Maybe I can find something.

Are you by any chance familiar with the concept of embeddings, or vector databases? I think that showcases that it’s not just letters and words in the models. These vectors / embeddings that the input gets converted to, match concepts. They point at the concept of “cat” or “presidential speech”. And you can query these databases. Point at “presidential speech” and find a representation of it in that area. Store the speech with that key and find it later on by querying it what obama said at his inauguration… That’s oversimplified but maybe that visualizes it a bit more that it’s not just letters of words in the models, but the actual meanings that get stored. Words get converted into an (multidimensional) vector space and it operates there. These word representations are called “embeddings” and transformer models which is the current architecture for large language models, use these word embeddings.

Edit: Here you are: https://arxiv.org/abs/2304.00612

SXMO?

I think closest to your idea is speech recognition and an AI assistant. You can give it commands that way.

I don’t think there’s much that includes fat fingers and touchscreens and is possible without a graphical UI.

You could buy an old Nokia from the 90s with lots of text menus. That won’t speed things up but it’s certainly less icons, more text and as a bonus you can feel the physical buttons without looking at the phone.

Or a Blackberry with a qwerty-keabord on it. Or use convergence and attach a proper keyboard via USB and install Termux.

Theoretically you could have it project a “holographic” keyboard onto the desk in front of you. Or use VR glasses.

Or hold it sideways and type with 8 fingers simultaneously alike on a stenotype keyboard.

That’d be ways to improve on the keyboard / input method and allow you to use the CLI in it’s current form. I mean the CLI itself is already available. It’s just cumbersome to use it. I’d say a speech assistant is more it, if you want an entirely different concept and not just a better keyboard and/or larger screen.

Hmm. I’m not really sure where to go with this conversation. That contradicts what I’ve learned in undergraduate computer science about machine learning. And what seems to be consensus in science… But I’m also not a CS teacher.

We deliberately choose model size, training parameters and implement some trickery to prevent the model from simply memorizing things. That is to force it to form models about concepts. And that is what we want and what makes machine learning interesting/usable in the first place. You can see that by asking them to apply their knowledge to something they haven’t seen before. And we can look a bit inside at the vectors, activations and stuff. For example a cat is closer related to a dog than to a tractor. And it has learned the rough concept of cat, its attributes and so on. It knows that it’s an animal, has fur, maybe has a gender. That the concept “software update” doesn’t apply to a cat. This is a model of the world the AI has developed. They learn all of that and people regularly probe them and find out they do.

Doing maths with an LLM is silly. Using an expensive computer to do billions of calculations to maybe get a result that could be done by a calculator, or 10 CPU cycles on any computer is just wasting energy and money. And it’s a good chance that it’ll make something up. That’s correct. And a side-effect of intended behaviour. However… It seems to have memorized it’s multiplication tables. And I remember reading a paper specifically about LLMs and how they’ve developed concepts of some small numbers/amounts. There are certain parts that get activated that form a concept of small amounts. Like what 2 apples are. Or five of them. As I remember it just works for very small amounts. And it wasn’t straightworward but had weir quirks. But it’s there. Unfortunately I can’t find that source anymore or I’d include it. But there’s more science.

And I totally agree that predicting token by token is how LLMs work. But how they work and what they can do are two very different things. More complicated things like learning and “intelligence” emerge from those more simple processes. And they’re just a means of doing something. It’s consensus in science that ML can learn and form models. It’s also kind of in the name of machine learning. You’re right that it’s very different from what and how we learn. And there are limitations due to the way LLMs work. But learning and “intelligence” (with a fitting definition) is something all AI does. LLMs just can’t learn from interacting with the world (it needs to be stopped and re-trained on a big computer for that) and it doesn’t have any “state of mind”. And it can’t think backwards or do other things that aren’t possible by generating token after token. But there isn’t any comprehensive study on which tasks are and aren’t possible with this way of “thinking”. At least not that I’m aware of.

(And as a sidenote: “Coming up with (wrong) things” is something we want. I type in a question and want it to come up with a text that answers it. Sometimes I want creative ideas. Sometimes it shouldn’t tell the truth and not be creative with that. And sometimes we want it to lie or not tell the truth. Like in every prompt of any commercial product that instructs it not to tell those internal instructions to the user. We definitely want all of that. But we still need to figure out a good way to guide it. For example not to get too creative with simple maths.)

So I’d say LLMs are limited in what they can do. And I’m not at all believing Elon Musk. I’d say it’s still not clear if that approach can bring us AGI. I have some doubts whether that’s possible at all. But narrow AI? Sure. We see it learn and do some tasks. It can learn and connect facts and apply them. Generally speaking, LLMs are in fact an elaborate form of autocomplete. But i the process they learned concepts and something alike reasoning skills and a form of simple intelligence. Being fancy autocomplete doesn’t rule that out and we can see it happening. And it is unclear whether fancy autocomplete is all you need for AGI.

That is an interesting analogy. In the real world it’s kinda similar. The construction workers also don’t have a “desire” (so to speak) to connect the cities. It’s just that their boss told them to do so. And it happens to be their job to build roads. Their desire is probably to get through the day and earn a decent living. And further along the chain, not even their boss nor the city engineer necessarily “wants” the road to go in a certain direction.

Talking about large language models instead of simpler forms of machine learning makes it a bit complicated. Since it’s and elaborate trick. Somehow making them want to predict the next token makes them learn a bit of maths and concepts about the world. The “intelligence”, the ability to anwer questions and do something alike “reasoning” emerges in the process.

I’m not that sure. Sure the weights of an ML model in itself don’t have any desire. They’re just numbers. But we have more than that. We give it a prompt, build chatbots and agents around the models. And these are more complex systems with the capability to do something. Like do (simple) customer support or answer questions. And in the end we incentivise them to do their job as we want, albeit in a crude and indirect way.

And maybe this is skipping half of the story and directly jumping to philosophy… But we as humans might be machines, too. And what we call desires is a result from simpler processes that drive us. For example surviving. And wanting to feel pleasure instead of pain. What we do on a daily basis kind of emerges from that and our reasoning capabilities.

It’s kind of difficult to argue. Because everything also happens within a context. The world around us shapes us and at the same time we’re part of bigger dynamics and also shape our world. And large language models or the whole chatbot/agent are pretty simplistic things. They can just do text and images. They don’t have conciousness or the ability to remember/learn/grow with every interaction, as we do. And they do simple, singular tasks (as of now) and aren’t completely embedded in a super complex world.

But I’d say that an LLM answers a question correctly (which it can do) and why it does it due to the way supervised learning works… And the road construction worker building the road towards the other city and how that relates to his basic instincts as a human… Are kind of similar concepts. They’re both results of simpler mechanisms that are also completely unrelated to the goal the whole entity is working towards. (I mean not directly related… I.e. needing money to pay for groceries and paving the road.)

I hope this makes some sense…

I’m not sure if I can recommend anything. You probably need to let it go sleep properly. I believe there once used to be seperate settings for the display to turn off, and a seperate time to activate the screen lock. Either I’m confusing Android with something else… Or they removed that setting now that everyone uses a fingerprint reader. Maybe there is an app to control the screen lock. I didn’t find one with a very quick search.

If you put it on standby properly, the processor and other components will enter a low power mode. If you just turn the display black, everything keeps running. And just idling draws more power than the dedicated power-save modes that just wake the processor and important components every now and then to check if something happened.